System and method for monitoring respiration

ABSTRACT

A system and method for monitoring respiration of a user, comprising: a respiration sensing module including a sensor configured to detect a set of respiration signals of the user based upon movement resulting from the user&#39;s respiration; a supplementary sensing module comprising an accelerometer and configured to detect a set of supplemental signals from the user; an electronics subsystem comprising a power module configured to power the system and a signal processing module configured to condition the set of respiration signals and the set of supplemental signals; a housing configured to facilitate coupling of the respiration sensing module and the supplementary sensing module to the user; and a data link coupled to the electronics subsystem through the housing and configured to transmit data generated from the set of respiration signals and the set of supplemental signals, thereby facilitating monitoring of the user&#39;s respiration.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.14/174,466, filed Feb. 6, 2014, which claims the benefit of U.S.Provisional Application Ser. No. 61/762,875, filed Feb. 9, 2013 and U.S.Provisional Application Ser. No. 61/873,698 filed Sep. 4, 2013, theentire disclosure of each of which is incorporated by reference in itsentirety

TECHNICAL FIELD

This invention relates generally to the biosignal monitoring devicefield, and more specifically to a new and useful system and method formonitoring respiration.

BACKGROUND

Respiration parameters can provide profound insight into an individual'swellbeing. Respiration parameters can be indicative of physiologicaland/or mental states of an individual, as well as prognostic with regardto diagnosis of medical conditions. In examples, respiration parameterscan provide insight into an individual's stress levels, and can beevidential of more serious pulmonary disorders, such as disordersassociated with chronic obstructive pulmonary disease (COPD). Traditionally, however, respiration monitoring has occurred in a clinicalsetting, contributing to the developing of respiration monitoringdevices that are motion-limiting, lack portability, and/or are difficultto use. There is thus a need in the biosignal monitoring device field tocreate a new and useful system for monitoring respiration. Thisinvention provides such a new and useful system and method.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 depicts an embodiment of a system for monitoring respiration of auser;

FIGS. 2A and 2B depict examples of a portion of a system for monitoringrespiration of a user;

FIGS. 3A and 3B depict examples of a system for monitoring respirationof a user;

FIGS. 4A and 4B depict examples of a system for monitoring respirationof a user;

FIG. 5 depicts an embodiment of a method for monitoring respiration of auser; and

FIGS. 6A-6D depict example outputs of an embodiment of a method formonitoring respiration of a user.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

The following description of the preferred embodiments of the inventionis not intended to limit the invention to these preferred embodiments,but rather to enable any person skilled in the art to make and use thisinvention.

1. System

As shown in FIG. 1, an embodiment of a system 100 for monitoringrespiration of a user comprises: a respiration sensing module nocomprising a sensor configured to detect a set of signals indicative ofa set of respiration characteristics of the user (i.e., respirationsignals); a supplementary sensing module 120 configured to detect asupplemental set of signals from the user; an electronics subsystem 130comprising a power module and a signal processing module, and configuredto process signals of the set of signals and the supplemental set ofsignals; and a housing 140 configured to house elements of the system100. Embodiments of the system 100 can further comprise a data storageunit 150 coupled to the electronics subsystem 130 and configured tostore data relevant to the respiration characteristics of the user; adata link 160 coupled to the electronics subsystem 130 and configured toprovide and/or receive data relevant to the set of respirationcharacteristics of the user; a processor 170 coupled to at least one ofthe data storage unit 150 and the data link 160 and configured togenerate an analysis based upon the set of respiration characteristicsof the user; and a user interface configured to inform the user basedupon the analysis.

The system 100 functions to detect signals indicative of a user'srespiration characteristics and to provide data relevant to the user'srespiration characteristics for further analysis, such that the user'srespiration behavior can be effectively monitored. The system 100 isalso preferably configured to provide information regarding the user'srespiration characteristics to the user and/or other entity at a userinterface. Analyses generated based upon the user's respirationcharacteristics can thus be used to inform the user of his/herrespiration behavior, and can additionally lead to a change in theuser's respiration behavior based upon the analyses provided to the userand/or other entity. Preferably, the user's respiration characteristicsare monitored by the system 100 substantially continuously and in realtime; however, the user's respiration characteristics can alternativelybe monitored intermittently and/or in non-real time.

The system 100 can function to monitor and/or indicate physiologicaland/or mental states of the user based upon the user's respirationcharacteristics, and can additionally or alternatively function tofacilitate diagnosis of medical conditions with pulmonary indications.In examples, the system 100 can facilitate monitoring and/or indicationof a user's stress levels and physical exertion (e.g., during exercise)based upon respiration characteristics. In other examples, the system100 can function to indicate signs of medical conditions, such asconditions associated with COPD (e.g., apnea, asthma, emphysema). In onesuch example, the system 100 can indicate a breathing abnormality of theuser, which can be used to initiate diagnosis of a condition of theuser's upper respiratory tract, trachea, bronchi, bronchioles, alveoli,pleura, pleural cavity, and/or any nerves or muscles associated withbreathing. The system 100 can, however, be configured to monitor anyother suitable respiration behavior of a user, and/or indicate any othersuitable sign of a respiration-related medical condition.

Preferably, the system 100 is configured to be worn by the user outsideof a clinical (e.g., hospital) or research (e.g., laboratory) setting,such that the user can be in a non-contrived environment as he or she isundergoing respiration monitoring. Additionally, the system 100preferably does not inhibit mobility of the user, such that respirationmonitoring can occur as the user performs normal activities (e.g.,walking, exercising, working, etc.) in his/her daily life. Furthermore,elements of the system 100 can be reusable or disposable, or the entiresystem 100 can be configured to be disposable. In one specific example,the system 100 is a unitized system 100 that couples to the user (e.g.,to the user's skin, to the user's clothing), thus not compelling thepatient to hold any part of the system 100 by hand; however, in thespecific example, the housing 140 is configured to reversibly couple anduncouple from other system elements, in order to provide modularity andversatility in coupling to a user. Furthermore, the system 100 ispreferably configured to monitor the user's respiration non-invasivelyand in a manner wherein the user is substantially removed fromclinical/research staff. Alternatively, the system 100 can besubstantially non-portable, non-wearable, and/or intended for use in aclinical or research setting.

1.1 Sensing Modules

The respiration sensing module no comprises a sensor configured todetect a set of signals indicative of a set of respirationcharacteristics (i.e., respiration signals) of the user, and functionsto sense movement of a portion of the user's body, wherein the movementresults from the user's respiration. The respiration sensing module nois preferably coupled directly to the user (e.g., to the user'sclothing, to the user's skin) in a manner that provides robust contactbetween the user and the respiration sensing module at a sensor-userinterface. After coupling, the sensor-user interface is preferablysubstantially fixed, such that motion detection associated withbreathing can be easily distinguished from any other motion (e.g., grossmotions of the user). The sensor-user interface is preferably locatedproximal to the user's torso (e.g., abdomen region, hip region, chestregion). Furthermore, the sensor-user interface is preferably defined asa region displaced in a superficial direction (e.g., along asuperficial-deep axis through the torso of the user); however, thesensor-user interface can alternatively be defined in any other suitablemanner. The sensor-user interface can be a substantially single point ofcontact on the user, can be defined as a planar surface between asurface of a sensor of the respiration sensing module and a surface ofthe user's body, and/or can be defined as a volume between a surface ofa sensor of the respiration sensing module and an opposing surface ofthe user's body. However, the sensor-user interface can be located atany suitable location relative to the user and can be defined relativeto the user in any other suitable manner. Alternatively, the sensor userinterface can be non-fixed, and the system 100 can be configured todistinguish motion of the user's body associated with breathing fromother detected motions (e.g., motion of the sensor relative to theuser's body, gross motions of the user).

Preferably, the sensor of the respiration sensing module 110 functionsbased upon respiratory inductance plethysmography (RIP), and preferablyfunctions to detect motions of the user's chest and/or abdominal wallproduced during the user's breathing. Additionally, the respirationsensing module 110 is preferably non-invasive in detecting signalsindicative of the user's respiration behavior; however, the respirationsensing module 110 can comprise invasive or minimally invasive elements.Alternatively, the respiration sensing module 110 can function basedupon any other suitable plethysmography-based sensing method, any othersuitable mechanical sensing method (e.g., acoustic sensing), and/or anysuitable sensing method (e.g., ultrasound respiration sensing).Additionally, the respiration sensing module 110 preferably detectssignals indicative of the user's respiration characteristicssubstantially continuously and in real time; however, the respirationsensing module 110 can alternatively or additionally detect signalsintermittently and/or not in real time.

In a first variation, the respiration sensing module 110 preferablycomprises a sensor including at least one element configured to deflectin response to movements of the user's body produced by the user'sbreathing, or to detect force in response to the user's breathing in anyother suitable manner (e.g., without deflection of an element). In thefirst variation, forces generated during the user's respiration, in adirection perpendicular to a surface of the respiration sensing module110 (i.e., at the sensor-user interface), are preferably detected by thesensor and used to determine characteristics of the user's respiration.As such, forces perpendicular to the sensor-user interface (e.g., alonga superficial-deep direction) and perpendicular to a surface of theuser's body can be used to determine aspects of the user's respiration.For example, the respiration sensing module does not require coupling tothe user by way of an element that wraps about the user's torso andtransmits tangential forces to the respiration sensing module 110 duringthe user's respiration. However, tangential forces generated at therespiration sensing module 110 during the user's respiration canadditionally or alternatively be used to determine characteristics ofthe user's respiration.

The element of the sensor is preferably configured to directly orindirectly (e.g., by way of a housing) provide a robust connection withthe user, such that deflections associated with the user's breathing aredetected with minimal interference due to other motions of the userand/or sensor. In the first variation, the respiration sensing modulecan include a sensing element (e.g., the sensor) that is constrained atopposing sides, in order to enhance an effect of respiration-inducedmotion of the user's body (e.g., abdominal region, chest region). In oneexample, the respiration sensing module can thus be positioned betweenthe user's clothing and the user's skin, coupled robustly to an articleof the user's clothing, and/or coupled to the user using any one or moreof an adhesive (e.g., permanent adhesive, non-permanent adhesive),strap, clip, or other suitable coupling element. In alternativeconfigurations, the sensing element of the respiration sensing modulecan be constrained at any other suitable number of sides and in anyother suitable configuration, such that the user's respiration can besensed at the sensing element.

In a first example of the first variation, the sensor comprises aforce-sensing resistor configured to generate a response in resistanceupon being subject to an applied force. In the first example, the forcesensing resistor is configured to provide a response in resistance(e.g., decrease in resistance) with an increase in applied force (e.g.,when the resistor is placed under compression). In a variation of thefirst example, the force sensing resistor is configured to provide aresponse in resistance (e.g., a decrease in resistance) with a decreasein applied force (e.g., when the resistor is placed under tension).However, in variations of the first example, the force sensing resistorcan additionally or alternatively be configured to provide any suitablechange decrease in applied force (e.g., when the resistor is placedunder tension). In the first example, the force-sensing resistorincludes a conductive polymer film (e.g., polymer thick film) includingelectrically conducting and non-conducting particles suspended inmatrix, coupled to a set of electrodes. Upon application of a force tothe matrix, conducting particles are moved in proximity and/or intocontact with the set of electrodes, adjusting a resistance of the filmin response to the applied force. In the first example, theforce-sensing resistor can be positioned between the user's clothing andthe user's body (e.g., at an abdomen region, at a chest region, betweenan undergarment and the user's body, etc.) and configured such thatapplication of a force to the resistor, in a direction perpendicular tothe surface of the user's body at the sensor-user interface, is detectedand produces a change in resistance. As such, the respiration sensingmodule 110 is able to produce electrical signals (e.g., resistancechanges) m response to compression/decompression of the sensor resultingfrom the user's breathing. In variations of the first example, thesensor can include multiple force-sensing resistors and/or other sensingelements, which can facilitate determination of additional aspects of anapplied force (e.g., centroid of force, etc.), for example, inapplications involving placement guidance for the respiration sensingmodule 110.

In a second example of the first variation, the sensor comprises acapacitor that is configured to produce an electrical signal (e.g.,change in electric field) in response to a deflection of a firstcapacitor plate relative to a second capacitor plate. The first and thesecond plates of the capacitor are separated in the second example by anon-rigid material that provides support to each plate of the capacitor.In the second example, the first and the second plates of the capacitorare preferably oriented with faces parallel to the surface of the userat the sensor-user interface, such that deflections perpendicular to thefaces of the capacitor plates, produced by breathing, are detected bythe respiration sensing module. As such, the capacitor plates can bepositioned between the user's clothing and the user's body (e.g., at anabdomen region, at a chest region, between an undergarment and theuser's body, etc.) and configured such that deflections of one capacitorplate relative to another capacitor plate, with deflection componentsperpendicular to the surface of the user's body at the sensor-userinterface, are detected. As such, the respiration sensing module 110 isable to produce electrical signals in response tocompression/decompression of the sensor resulting from the user'sbreathing. In a variation of the second example, the capacitor can be afluid capacitor coupled to a pressure sensor, such thatdeflection/deformation of the fluid capacitor produces a detectablechange in pressure at the pressure sensor, which results in a detectedelectrical signal indicative of the user's respiration. In variations ofthe second example, the sensor can include multiple capacitive elementsand/or other sensing elements, which can facilitate determination ofadditional aspects of an applied force (e.g., centroid of force, etc.),for example, in applications involving placement guidance for therespiration sensing module 110.

In a third example of the first variation, as shown in FIG. 2A, thesensor comprises a magnetic element and a hall-effect sensor, wherein achange in magnetic field, produced by deflection of the magneticelement, is detected by the hall-effect sensor and produces anelectrical signal indicative of the user's respiration. In the thirdexample, the magnetic element is separated from the hall-effect sensorby a nonrigid material or structure, which can include a spring-loadedplatform or elastomeric material (e.g., silicon-based material) to whichthe magnetic element is coupled (e.g., embedded, attached, etc.). In thethird example, the magnetic element and the hall-effect sensor arepositioned between the user's clothing and the user's body (e.g., at anabdomen region, at a chest region, between an undergarment and theuser's body, etc.) and configured such that deflections of the magneticelement relative to the hall-effect sensor, with deflection componentsperpendicular to the surface of the user's body at the sensor-userinterface, are detected. As such, the respiration sensing module 110 isable to produce electrical signals in response tocompression/decompression of the sensor resulting from the user'sbreathing. In variations of the third example, the sensor can includemultiple hall-effect sensors and/or other sensing elements, which canfacilitate determination of additional aspects of an applied force(e.g., centroid of force, etc.), for example, in applications involvingplacement guidance for the respiration sensing module 110.

In a fourth example of the first variation, as shown in FIG. 2B, thesensor is a piezoelectric sensor that produces an electrical signal inresponse to deformation of a piezoelectric material of the sensor. Thepiezoelectric sensor in the fourth example can be flexible and embeddedin an article of the user's clothing (e.g., bra, waistband, belt) orpositioned between the user's body and an article of clothing, such thatmotion of the user, produced by respiration, deforms the piezoelectricmaterial and produces an electrical signal indicative of the user'srespiration. In the fourth example, the piezoelectric sensor is thin andcharacterized by a low-aspect ratio, as shown in FIG. 2B, in order tofacilitate deformation of the piezoelectric material to provide greatersensitivity. In other variations of the fourth example, thepiezoelectric sensor can be characterized by any suitable morphologyand/or profile. In variations of the fourth example, the sensor caninclude multiple piezoelectric elements and/or other sensing elements,which can facilitate determination of additional aspects of an appliedforce (e.g., centroid of force, etc.), for example, in applicationsinvolving placement guidance for the respiration sensing module 110.

In another variation, the respiration sensing module 110 canadditionally or alternatively comprise a mechanical sensing element,which mechanically detects the user's respiration. In an example, therespiration sensing module 110 can comprise an acoustic sensor (e.g.,microphone) configured to detect acoustic signals indicative of theuser's respiration. In another example, the respiration sensing module110 can comprise a mechanical deformation sensor (e.g., strain gage)configured to deform to mechanically detect the user's respiration.Other examples can comprise any other suitable sensor configured tomechanically detect signals indicative of the user's respiration.

In yet another variation, the respiration sensing module 110 canadditionally or alternatively comprise an ultrasound transducer (e.g.,ultrasound proximity sensor) configured to ultrasonically detect signalsindicative of the user's respiration. The ultrasound transducer cancomprise a set of ultrasound emitters configured to emit acousticsignals toward the user and a set of ultrasound receivers configured toreceive acoustic signals from the user, wherein the received signals areindicative of motions of the user's abdomen and/or chest produced duringbreathing. The respiration sensing module 110 can, however, comprise anysuitable combination of any of the above variations and examples, and/orcombinations of any variation or example with any other suitablerespiration sensing module. For example, the respiration sensing module110 can comprise multiple sensor types and/or multiples of a singlesensor type to provide redundancy in means for respiration signaldetection.

The set of respiration characteristics characterized in the set ofrespiration signals preferably comprises any one or more of: respirationrate (e.g., breaths per second), depth of breath, shallowness of breath,inhalation-to-exhalation ratio, thoracic variations, tidal volume (or anestimation thereof), inspiratory flow (e.g., peak value, mean value),expiratory flow (e.g., peak value, mean value), fractional inspiratorytime, work of breathing, phase angle, respiration waveform morphology(e.g., shape, area under waveform, regularity of waveform, etc.), anyother suitable respiration characteristic, and any other suitablederivative of a respiration characteristic. With regard to respirationwaveform morphology, respiration characteristics can include, forexample, a sharpness of a transition between inhalation and exhalationfor a user, as indicated by the respiration waveform, a length of breathholding by the user, as indicated by the respiration waveform, or anyother suitable factor. Additionally, the set of respirationcharacteristics can indicate respiration events associated withlaughter, sighing, wheezing, coughing, apnea, and/or any other suitableevent associated with the user's respiration.

The supplementary sensing module 120 is configured to detect asupplemental set of signals from the user, and functions to provideadditional data that facilitates processing of the set of signalsindicative of the set of respiration characteristics. As such, thesupplementary sensing module 120 can enable extraction of a set ofrespiration characteristics from the set of respiration signals, by wayof distinguishing signals characterizing the user's respiration fromsignals not characterizing the user's respiration. The supplementarysensing module can additionally function to provide additional data thatcan enrich analyses by detecting other signals from the user and/or theuser's environment. The supplementary sensing module 120 preferablycomprises an accelerometer, and in some variations, can additionally oralternatively comprise a gyroscope. In other variations, thesupplementary sensing module 120 can further comprise a globalpositioning sensor (GPS) that provides location data for the user. Instill other variations, the supplementary sensing module 120 canadditionally or alternatively comprise additional sensors for pulseeximetry and/or electrocardiography. As such, the supplementary sensingmodule 120 can be configured to facilitate extraction of one or more of:the user's posture, the user's activity, the user's location, biometricsignals from the user, and any other suitable signal of the user relatedto the user's activity, state, and/or respiration.

In variations of the supplementary sensing module 120 comprising anaccelerometer, data from the accelerometer can be used to distinguishmotion of the user not associated with the user's respirationcharacteristics from motion of the user associated with the user'srespiration characteristics. For example, motion of the user associatedwith walking or exercising may produce signal detection at therespiration sensing module 110, and the accelerometer can be used toseparate interfering data resulting from walking or exercising from datadirectly associated with the user's respiration characteristics. Assuch, the accelerometer data can be used to filter out interfering datain order to extract data relevant to the user's respirationcharacteristics. The accelerometer can be a single axis accelerometer,but can also be a dual- or triple-axis accelerometer. Furthermore, datafrom the accelerometer can function to provide enriching data associatedwith, for example, the user's posture (e.g., upright, laying down,slouching, sitting, etc.) and/or the user's activity (e.g., exercise,resting, sleeping, etc.).

In variations of the supplementary sensing module 120 comprising agyroscope, data from the gyroscope can be used to distinguish motion ofthe user not associated with the user's respiration characteristics frommotion of the user associated with the user's respirationcharacteristics. The gyroscope thus functions to detect orientation ofthe system 100, which can be used to facilitate data processing and/orcan be used to enrich data for further analyses. For example, motion ofthe user associated with laying down or sitting upright may producesignal detection at the respiration sensing module 110, and thegyroscope can be used to separate interfering data resulting from layingdown or sitting upright from data directly associated with the user'srespiration characteristics. As such, the gyroscope data can be used tofilter out interfering data in order to extract data relevant to theuser's respiration characteristics. The gyroscope can be a single axisaccelerometer, but can also be a dual- or triple-axis gyroscope.Furthermore, data from the gyroscope can function to provide enrichingdata associated with, for example, the user's posture (e.g., upright,laying down, slouching, sitting, etc.) and/or the user's activity (e.g.,exercise, resting, sleeping, etc.).

In variations comprising a GPS, data from the GPS can be used to providelocation data for the system 100 and/or the user, which can be used toenrich data detected and collected at the respiration sensing module no.In one example, data from the GPS can indicate that the user is at agym, and can be used to provide a label or tag for respiration signalscollected while the user is at the gym. In another example, data fromthe GPS can indicate that the user is in a stressful environment (e.g.,examination room, hospital, etc.) and can be used to provide a label ortag for respiration signals collected while the user is in the stressfulenvironment. In yet another example, data from the GPS can indicate thatthe user is in a non-stressful environment (e.g., restaurant, home) andcan be used to provide a label or tag for respiration signals collectedwhile the user is in the non-stressful environment. Data from the GPSand/or other sensors of the supplementary sensing module 120 canadditionally or alternatively be used to guide the user in monitoringhis/her respiration behavior once the system 100 detects that the useris in any suitable environment. For example, data from the GPS can beused to guide the user's breathing behavior once the GPS and/oraccelerometer has indicated that the user is exercising.

The supplementary sensing module 120 can, however, comprise any othersuitable sensor or combination of sensors for providing additional datarelevant to monitoring a user's respiration behavior. Furthermore, thesupplementary sensing module 120 and/or any other suitable element ofthe system 100 can be configured to automatically or manually receivepersonal preference information from the user, as described in Section 2below.

1.2 Electronics Subsystem

As shown in FIG. 1, the electronics subsystem 130 comprises a powermodule 131 and a signal processing module 135, and is configured toprocess signals of the set of signals and the supplemental set ofsignals. The electronics subsystem 130 can thus receive an input from atleast one of the respiration sensing module no and the supplementarysensing module 120, and functions to process the input for furtheranalysis in order to facilitate monitoring of the user's respiration.

The power module 131 of the electronics subsystem 130 functions toprovide regulated and unregulated electrical power to the system 100 andto allow power storage for the system 100. The power module 131preferably comprises a lithium battery that is configured to berechargeable, but can alternatively comprise any other suitablerechargeable battery (e.g., nickel-cadmium, metal halide, nickel metalhydride, or lithium-ion polymer). Alternatively, the power module 131can comprise a non-rechargeable battery (e.g., alkaline battery) thatcan be replaced to further enhance modularity in the system 100.Preferably, the power module 131 145 is configured to have a profilewith a low aspect ratio, contributing to a thin form factor of thesystem 100. However, the power module 131 can be configured to have anyappropriate profile such that the power module 131 provides adequatepower characteristics (e.g., cycle life, charging time, discharge time,etc.) for the system 100.

In variations where the battery of the power module 131 is rechargeable,the electronics subsystem 130 can also comprise a coil of wire 132 andassociated electronics that function to allow inductive coupling ofpower between an external power source and the power module 131, inorder to enable wireless charging. The charging coil 132 preferablyconverts energy from an alternating electromagnetic field (e.g.,provided by a charging dock), into electrical energy to charge thebattery. Inductive charging provided by the charging coil 132 thus alsofacilitates user mobility while interacting with the system 100, suchthat the user can be extremely mobile while his/her respiration is beingmonitored. In alternative variations, however, the charging coil 132 canbe altogether omitted (e.g., in variations without a rechargeablebattery), or replaced or supplemented by a connection (e.g., USBconnection) configured to provide wired charging of a rechargeablebattery.

The signal processing module 135 of the electronics subsystem 130 ispreferably coupled to the respiration sensing module 110 and thesupplementary sensing module 120 and functions to condition sets ofsignals detected by the system 100. Outputs of the signal processingmodule 135 can be further processed in order to generate analysesrelevant to monitoring of the user's respiration. The signal processingmodule 135 thus preferably comprises a microcontroller, and canadditionally comprise or be coupled to any other suitable element(s),such as an amplifier, a filter, and/or an analog-to-digital converter(ADC).

In variations of the signal processing module 135 comprising amicrocontroller, the microcontroller is preferably configured to controlpowering of the system 100, handling of signals received by the system100, distribution of power within the system 100, and/or any othersuitable function of the system 100. The control module can beconfigured to perform at least a portion of the method described Section2 below, but can additionally or alternatively be configured to performany other suitable method that facilitates respiration monitoring for auser. In some variations, the microcontroller can be preconfigured toperform a given method, with the system 100 configured such that themicrocontroller cannot be reconfigured to perform a method differentfrom or modified from the given method. However, in other variations ofthe system 100, the microcontroller can be reconfigurable to performdifferent methods.

In variations of the signal processing module 135 comprising anamplifier, the amplifier functions to amplify a signal, in order tofacilitate signal processing by the system 100. The system can compriseany suitable number of amplifiers, depending upon the configuration ofthe amplifier(s) relative to other elements (e.g., multiplexers) of theelectronics subsystem 130. In one variation, the amplifier is placedafter a multiplexer in order to amplify a single output line. In anothervariation, a set of amplifiers is placed before a multiplexer, in orderto amplify multiple input channels into the multiplexer. In yet anothervariation, the electronics subsystem 130 comprises amplifiers before andafter a multiplexer, in order to amplify input and output lines of themultiplexer. The amplifier can also be coupled to a filter configured tosuppress inter-channel switching transients (e.g., produced duringmultiplexing), and/or any other undesirable signals. In variations, theelectronics subsystem 130 can comprise a low pass filter, a high passfilter, and/or a band pass filter configured to only allow passage of acertain range of signals, while blocking other signals (e.g.,interference, noise) outside of the range of signals. The electronicssubsystem 130 can additionally comprise an ADC, which functions toconvert analog signals (e.g., biosignals detected by the set of sensors,amplified signals, filtered signals) into a digital quantization. Theelectronics system 130 can comprise any suitable number of ADCs forconversion of analog signals (e.g., from multiple channels) into digitalquantizations. Furthermore, the electronics system 130 can comprise anyother suitable element(s) for signal processing/conditioning.

1.3 Housing

As shown in FIG. 1, the system 100 also comprises a housing 140configured to enclose at least a portion of the system 100. The housing140 can also be configured to reversibly couple to elements of thesystem 100 (e.g., the respiration sensing module, the supplementarysensing module, and the electronics subsystem), such that the system 100is a modular system. The housing 140 functions to protect elements ofthe system 100 over the lifetime usage of the system 100, and canfurther function to enhance wearability of the system 100. The housing140 is preferably configured to clip to an article of a user's clothing,such that the housing can reversibly couple to the user's clothing andcan be repositionable relative to the user. However, the housing 140 canadditionally or alternatively be configured to couple to the user and/orthe user's clothing in any other suitable manner. In one variation, thehousing is integrated into an article of the user's clothing (e.g.,proximal to the chest region, proximal to the abdominal region) and inan example of this variation, the housing 140 is embedded into theuser's clothing (e.g., bra, waistband, belt) in a semi-permanent manner.

The housing 140 is preferably rigid; however, the housing canalternatively be flexible in order to enhance user comfort wheninterfacing with the system 100. To facilitate modularity, the housing140 preferably defines or comprises a mechanism that enables reversiblecoupling to other elements of the system 100. In one example, thehousing 140 can comprise a recess or a protrusion configured to coupleto a corresponding protrusion or recess, respectively, of anotherelement of the system 100. In another example, the housing 140 can beconfigured to snap-fit or press-fit with another element of the system100 based upon mutual compliance between coupling elements. In yetanother example, the housing can be configured to couple based uponfriction with and/or adhesion to another element. In some variations,the housing 140 can also be configured to provide an electrical couplingwith another element of the system 100. For example, the housing 140 canbe configured to couple to the sensing modules 110, 120, and provide anelectromechanical coupling between the sensing modules 110, 120 and theelectronics subsystem 130. Furthermore the housing can also bewater-resistant or waterproof, such that washing of the housing 140 doesnot damage the housing. As such, the housing 140 is preferably composedof a plastic material, but can alternatively be composed of any othersuitable material (e.g., polymer, rubber, metal, ceramic).

In examples, as shown in FIGS. 3A-4B the housing 140 is plastic andcomprises a clip 142 that is configured to couple to the user'sclothing. In this example, the housing comprises a clip 142 componentthat is configured to reversibly couple to a unit housing the sensingmodules 110, 120 and the electronics subsystem 130, such that thesensing modules 110, 120 and the electronics subsystem 130 can bereplaced easily, if necessary. Furthermore, in this example, the clip142 component is configured to electromechanically couple to the unithousing the sensing modules 110, 120 and the electronics subsystem 130,such that a data link can be coupled, through the clip component, to theelectronics subsystem. In another example, multiple instances of thehousing 140 are integrated into various articles of the user's clothing,wherein each housing instance is configured to reversibly couple to aunit comprising the sensing modules 110, 120 and the electronicssubsystem 130. As such, the user can reversibly couple the same unitcomprising the sensing modules 110, 120 and the electronics subsystem130 to different articles of his/her clothing, in order to takeadvantage of system 100 modularity and to provide user convenience. Thehousing can, however, be configured in any other suitable manner.

1.4 System—Other Elements

As shown in FIG. 1, the system 100 can further comprise a data storageunit 150 coupled to the electronics subsystem 130, which functions tostore data relevant to the respiration characteristics of the user. Thedata storage unit 150 can be implemented with the electronics subsystem130, mobile device, personal computer, web browser, external server(e.g., cloud), and/or local server, or any combination of the above, ina network configured to transmit, store, and receive data. Preferably,data from the data storage unit 150 is automatically transmitted to anyappropriate external device continuously; however, data from the datastorage unit 150 can alternatively be transmitted intermittently (e.g.every minute, hourly, daily, or weekly).

Also shown in FIG. 1, the system 100 can further comprise a data link160, coupled to the electronics subsystem 130 (e.g., through thehousing, through a clip component), which functions to transmit anoutput of at least one element of the electronics subsystem 130 to amobile device, other computing module (e.g., desktop computer, laptopcomputer, tablet, smartphone, health tracking device, cloud), and anysuitable input to the electronics subsystem 130. Preferably, the datalink 160 is a wireless interface; however, the data link 160 canalternatively be a wired connection. In a first variation, the data link160 can include a Bluetooth module that interfaces with a secondBluetooth module included in the mobile device 161 or external element,wherein data or signals are transmitted by the data link 160 to/from themobile device or external element over Bluetooth communications. Thedata link 160 of the first variation can alternatively implement othertypes of wireless communications, such as 3G, 4G, radio, or Wi-Ficommunication. In the first variation, data and/or signals arepreferably encrypted before being transmitted by the data link 160. Forexample, cryptographic protocols such as Diffie-Hellman key exchange,Wireless Transport Layer Security (WTLS), or any other suitable type ofprotocol may be used. The data encryption may also comply with standardssuch as the Data Encryption Standard (DES), Triple Data EncryptionStandard (3-DES), or Advanced Encryption Standard (AES).

In a second variation, the data link 160 is a wired connection, whereinthe data link includes a wired jack connector such that the electronicssubsystem 130 can communicate with the mobile device and/or any externalcomputing element through an audio jack of the mobile device and/orexternal computing element. In one specific example of the data link 160that includes a wired jack, the data link 160 is configured only totransmit output signals from the electronics subsystem 130. In anotherspecific example, the data link 160 is configured to transmit data toand from at least one element of the electronics subsystem 130 and amobile device/external computing module (e.g., cloud). In this example,the data link 160 can transmit output signals into the mobile devicethrough the microphone input of the audio jack of the mobile device andcan retrieve data from the audio output of the audio jack of the mobiledevice. In this example, the data link 160 can be configured tocommunicate with the mobile device via inter-integrated circuitcommunication (I2C), one-wire, master-slave, or any other suitablecommunication protocol. However, the data link 160 can transmit data inany other way and can include any other type of wired connection (suchas a USB wired connection) that supports data transfer between theelectronics subsystem 130, the mobile device, and/or any other suitablecomputing element.

As shown in FIG. 3-A, the system 100 can also further comprise a usernotification subsystem 165, which functions to provide a usernotification to the user interfacing with the system 100, as describedin Section 2 below. The user notification subsystem 165 is preferablycoupled to the electronics subsystem 130; however, the user notificationsubsystem 165 can additionally or alternatively be configured relativeto the system 100 in any other suitable manner. In variations, the usernotification subsystem 165 is configured to provide one or more of: ahaptic notification, a visual notification, an auditory notification,and any other suitable type of notification. As such, in specificexamples, the user notification subsystem 165 can include one or moreof: a vibration motor, as shown in FIG. 3A, a display, and a speaker.

The system 100 can also further comprise a processor 170 configured togenerate an analysis based upon at least one of the set of signalsreceived at the respiration sensing module 110, the supplementarysensing module 120, and an output of the electronics subsystem 130. Invariations, the processor 170 can be configured to perform at least aportion of an embodiment of the method 200 described in Section 2 below;however, in other variations, the processor 170 can be configured toperform any other suitable method. The processor 170 can be implementedin any suitable computing module (e.g., mobile device, personalcomputer, cloud, etc.). The processor 170 thus functions to perform atleast a portion of the method 200 described in Section 2 below, and toprovide an analysis that can be used to inform the user of his/herrespiration behavior in order to provide interactive respirationmonitoring for the user. During generation of the analysis, theprocessor 170 can be configured to associate respiration events (e.g.,coughing, laughing, wheezing, apnea, sighing) and/or other user events(e.g., user activities) captured in the set of signals, based upon datafrom the sensor(s) of the respiration sensing module 110 and/or thesupplementary sensing module (e.g., accelerometer, gyroscope, GPS). Theanalysis can comprise a generated metric that generally informs the userof his/her respiration behavior quality, in relation to respirationevents and/or user events, and can additionally or alternativelycomprise metric(s) that quantify respiration characteristics (e.g.,rate, flow parameters, inhalation-to-exhalation ratio, etc.) of the userin relation to respiration events and/or user events. Based upon thegenerated analysis, the processor 170 can also be configured to providea user notification (e.g., recommendation) to the user that affectshis/her respiration behavior, such that the processor facilitates achange in the user's respiration behavior. As such, at least one of theanalysis, metric(s), and recommendation can be provided to the user at auser interface in any suitable manner (e.g., audibly, visually,haptically). Thus, in examples, an output of the processor 170 can beused to provide a notification to the user by way of at least one of aspeaker, a visual display, and a vibration motor, as described above. Inone such example, the notification can be provided to the user at amobile device of the user. The processor 170 can, however, be configuredto provide feedback to the user in any other suitable manner.Furthermore, variations of the processor 170 can be configured toimplement a machine learning algorithm (e.g., supervised, unsupervised)configured to identify respiration signatures of the user, such thatanalysis of the set of respiration signals improves with the quantity ofrespiration data acquired from the user. In some variations, the machinelearning algorithm can also be trained with a set of exemplary dataconfigured to provide a base set of features configured to train thealgorithm to distinguish certain base traits from the respirationwaveform. Furthermore, the algorithm can be adapted to a respirationsignals from a single user, and/or signals from multiple users.

As a person skilled in the field of biosignal monitoring devices willrecognize from the previous detailed description and from the figuresand claims, modifications and changes can be made to the embodiments,variations, examples, and specific applications of the system 100described above without departing from the scope of the system 100.

2. Method

As shown in FIG. 4, an embodiment of a method 200 for monitoringrespiration of a user comprises: receiving a set of respiration signalsfrom the user S210; receiving a set of supplementary signals configuredto facilitate extraction of a set of respiration characteristics fromthe set of signals S220; generating a dataset from the set of signalsand the set of supplementary signals S230; automatically associating auser event with a portion of the dataset, based upon a feature extractedfrom at least one of the set of respiration signals and the set ofsupplementary signals S240; generating a metric from the portion of thedataset and a comparative metric from the dataset S250; generating ananalysis based upon the user event, the metric, and the comparativemetric S260; and providing a user notification to the user based uponthe analysis S270. The method 200 can further comprise providing themetric, the trend in the metric, and the association to at least one ofthe user and a second entity S280, which can enable a second entity tofacilitate monitoring of the user's respiration behavior. The method 200can be used to facilitate monitoring of the respiration of the user, andcan further function to assist the user in modifying his or her behaviorto adjust his/her respiration behavior in a beneficial way.

Block S210 recites: receiving a set of respiration signals from theuser, and functions to receive a set of signals from the user, in orderto generate respiration data and/or metrics that can be used to monitorthe user's respiration. Block S210 is preferably implemented using anembodiment of the system 100 described in Section 1 above, and more,specifically, using a variation of the respiration sensing moduledescribed above; however, Block S210 can be implemented using anysuitable sensor system configured to detect respiration signals from auser. The set of respiration signals in Block S210 is preferablyreceived and transmitted continuously and substantially in real time;however, the set of signals can alternatively be received andtransmitted noncontinuously and/or in non-real time. Preferably, the setof respiration signals is received within a time window (e.g. a minutetime window, an hour time window, a 24-hour time window) spanning a setof time points, such that the user's respiration behavior can bemonitored over the time window in order to link an analysis generatedfrom the set of signals to a time window that is relevant to the user.

In some variations, Block S210 can include providing a task to the userS212, wherein the task facilitates provision and/or reception of the setof respiration signals from the user. In one variation, the task can beprovided by way of an application executing on a computing device of theuser (e.g., mobile device, tablet, personal computer, etc.), wherein thecomputing device is coupleable to an embodiment of a system thatreceives the set of set of respiration signals. Additionally, provisionof the task is preferably performed substantially concurrently withreception of the set of respiration signals, such that the set ofrespiration signals and the task are substantially synchronized.However, the task can be provided in any other suitable manner, usingany other suitable system, and/or without temporal synchronization.

The task preferably enables the user to modulate his/her respiratorystate, which can indirectly and/or directly affect any other suitableneurocognitive and/or physiological state of the user. In variations,the task can function to affect any one or more of: the user's focus,the user's attention, the user's mental stress level, the user'sphysiological stress level, the user's fatigue, the user's balance, theuser's cardiovascular health, the user's respiratory health, and anyother suitable neurocognitive and/or physiological state of the user. Inone example, the task can be provided in the form of a game executing ona mobile device of the user, wherein the game assists the user inachieving a desired and/or beneficial respiration state. In the example,the game can thus provide feedback to the user, in order to modulate arespiration state of the user. In specific examples, the game caninstruct the user to maintain a position of an animated object (e.g., afeather, a pendulum, a teeter-totter) rendered at a display of themobile device, wherein the user maintains the position of the animatedobject by adjusting a respiration parameter (e.g., rate of respiration,respiration waveform profile, etc.). A user's performance of the taskcan thus be determined based upon a duration over which the usermaintains a desired respiration state, a variance metric (e.g., standarddeviation, variance) characterizing variations in the user's respirationstate, a sociocomparative metric characterizing the user's performanceof the task relative to past performances by the user and/or to one ormore additional users, and/or any other suitable performance metric.

Block S220 recites: receiving a set of supplementary signals configuredto facilitate extraction of a set of respiration characteristics fromthe set of respiration signals, and functions to provide additional datathat facilitates processing of the set of respiration signals indicativeof the set of respiration characteristics. Block S220 can enabledistinguishing of signals characterizing the user's respiration fromsignals not characterizing the user's respiration and can provideadditional data that can enrich analyses by taking into account otherdata from the user and/or the user's environment. Block S220 canadditionally or alternatively enable generation and/or provision ofnotifications to the user, as described below with respect to BlockS270. Block S220 is preferably implemented using an embodiment of thesystem 100 described in Section 1 above, and more, specifically, using avariation of the supplementary sensing module comprising at least one ofan accelerometer, a gyroscope, and a GPS described above; however, BlockS220 can be implemented using any suitable sensor system configured todetect supplementary signals from a user. Similar to Block S210, the setof supplementary signals in Block S220 is preferably received andtransmitted continuously and substantially in real time; however, theset of supplementary signals can alternatively be received andtransmitted non-continuously and/or in non-real time. Furthermore, theset of supplementary signals can be received automatically, and/ormanually (e.g., upon user input, upon input by another entity).Preferably, the set of supplementary signals is also received within atime window (e.g. a minute time window, an hour time window, a 24-hourtime window) spanning a set of time points.

In one variation, the set of supplementary signals can be provided, atleast in part, by the user providing the set of respiration signals. Inthis variation, the set of supplementary signals can include informationprovided by the user, wherein the information indicates personalpreferences of the user, with regard to performing activities that canaffect a respiration, neurocognitive, and/or other physiological stateof the user. In one example, the information provided by the user caninclude any one or more of: dietary preferences (e.g., favorite foods,favorite restaurants, food allergies, etc.), exercise preferences (e.g.,favorite gym locations, favorite types of exercise), activitypreferences to reduce stress (e.g., reading, watching movies,socializing, etc.), and any other suitable preference of the user. Theinformation contributing to the set of supplementary signals can then beused, for instance, to provide personalized notifications to the user(e.g., in Block S270), and/or for any other suitable purpose to affectthe user's respiration. In this variation, the information can beretrieved manually, for instance, based upon input provided by the userand/or another entity associated with the user at an input module (e.g.,keyboard, keypad, touchscreen, voice detection module, etc.).Additionally or alternatively, the information can be retrievedautomatically, for instance, based upon accessing of the user's socialnetworks for status updates, location check-ins, reviews of vendors,reviews of service providers, and any other suitable social network.Additionally or alternatively, the information can be retrievedautomatically using sensors configured to detect one or more of: theuser's food/beverage consumption (e.g., spectophotometers), the user'sactivity level (e.g., accelerometers, gyroscopes), the user's location(e.g., GPS elements), and/or any other suitable sensor.

In some variations, the set of supplementary signals received in BlockS220 can be used to distinguish motion of the user not associated withthe user's respiration characteristics from motion of the userassociated with the user's respiration characteristics, based uponaccelerometer and/or gyroscope signals. For example, motion of the userassociated with laying down or sitting upright may produce signaldetection at a respiration sensing module in an example of Block S210,and signals from a supplementary sensing module used in Block S220 canbe used to separate interfering signals resulting from laying down orsitting upright from data directly associated with the user'srespiration characteristics. Additionally or alternatively, in somevariations, the set of supplementary signals can be used to enrich theset of data generated in Block S230. In one example, signals from a GPSof a supplementary sensing module can indicate that the user is at agym, and can be used to provide a label or tag for respiration signalscollected while the user is at the gym. In another example, signals froman accelerometer of a supplementary sensing module can indicate that theuser is running, and can be used to provide a label or tag forrespiration signals collected while the user is running. In yet anotherexample, signals from a gyroscope of a supplementary sensing module canindicate that the user is lying down, and can be used to provide a labelor tag for respiration signals collected while the user is resting. Assuch, supplementary signals can be used to additionally or alternativelyidentify activities and/or events of the user, that can be associatedwith data generated from the set of respiration signals and/or the setof supplementary signals.

The set of respiration characteristics characterized in the set ofrespiration signals and extracted using the set of supplementary signalspreferably comprises any one or more of: respiration rate (e.g., breathsper second), depth of breath, shallowness of breath,inhalation-to-exhalation ratio, thoracic variations, tidal volume (or anestimation thereof), inspiratory flow (e.g., peak value, mean value),expiratory flow (e.g., peak value, mean value), fractional inspiratorytime, work of breathing, phase angle, respiration waveform morphology(e.g., shape, area under waveform, regularity of waveform, etc.), anyother suitable respiration characteristic, and any other suitablederivative of a respiration characteristic. With regard to respirationwaveform morphology, Block S210 and/or Block S220 can enablecharacterization of respiration characteristics, including, for example,a sharpness of a transition between inhalation and exhalation for auser, as indicated by the respiration waveform, a length of breathholding by the user, as indicated by the respiration waveform, or anyother suitable factor. Additionally, the set of respirationcharacteristics received can indicate respiration events associated withlaughter, sighing, wheezing, coughing, apnea, and/or any other suitableevent associated with the user's respiration. In some variations,extraction of the set of respiration characteristics can includeimplementing a machine learning algorithm (e.g., supervised,unsupervised) configured to identify respiration signatures of the user,such that analysis of the set of respiration signals improves with thequantity of respiration data acquired from the user. In some variations,the machine learning algorithm can also be trained with a set ofexemplary data configured to provide a base set of features configuredto train the algorithm to distinguish certain base traits from therespiration waveform. Furthermore, the algorithm can be adapted to arespiration signals from a single user, and/or signals from multipleusers.

Block S230 recites: generating a dataset derived from the set ofrespiration signals and the set of supplementary signals, and functionsto convert signals received in Blocks S210 and S220 into a set ofquantitative data for determining a metric characterizing the user'srespiration. Preferably, Block S230 includes transforming an electricalsignal (e.g., resistance, voltage, impedance, or capacitance), producedby an embodiment of a sensing module described above, into a set ofquantitative parameters. Preferably, the set of quantitative parametersis generated at time points within a given time window (e.g., duringwhich respiration and/or supplementary signals are received), in orderto facilitate generation of a trend in a metric, based upon at least onerespiration characteristic of the set of respiration characteristicscharacterizing the user's respiration. Also, the dataset preferablyincludes data from which absolute values and changes in value of atleast respiration characteristic of the set of respirationcharacteristics can be extracted. In an example, for each time point ofa time window for signal collection, the dataset captures a value ofrespiration rate (e.g., breaths per second), depth of breath,shallowness of breath, inhalation-to-exhalation ratio, thoracicvariations, tidal volume (or an estimation thereof), inspiratory flow,expiratory flow, work of breathing, phase angle, respiration waveformmorphology (e.g., shape, area under waveform, regularity of waveform,etc.), any other suitable respiration characteristic, and any othersuitable derivative of a respiration characteristic. Additionally, thedataset can include qualitative data, such as qualifiers characterizingdesired ranges of values for a given respiration characteristic (e.g.,within target range, below target range, above target range).

Block S240 recites: automatically associating a user event with aportion of the dataset, based upon a feature extracted from at least oneof the set of respiration signals and the set of supplementary signals,and functions to identify and tag a user event within the dataset. Assuch, Block S240 can associate user events (e.g., activities,respiration events) with portions of the dataset characterizing at leastone respiration characteristic of the set of respirationcharacteristics. The user event can define a user activity (e.g.,exercise, rest, sleep) from supplementary signal data, a userorientation (e.g., slouching, sitting, laying down) from supplementarysignal data, a user location from supplementary signal data, and/or auser respiration event (e.g., apnea, laughing, coughing, wheezing) fromrespiration signal data and/or supplementary signal data. The user eventcan additionally or alternatively be derived from accessing electronicinformation of the user, including information accessible by socialnetworks of the user. For instance, status updates, check-ins, and/orany other suitable information, derived from social networks of theuser, can be used to determine the user event(s). As such,characteristic events identified from the respiration signals and/or thesupplementary signals can be automatically tagged in the dataset inorder to create unique signatures for user events. As shown in FIGS.5A-5D, the user event can comprise a signal feature that is identifiablewithin the set of data, based upon signal pattern, signal amplitude,signal frequency, signal repetition, signal uniformity, etc. In examplesshown in FIGS. 5A-5D, signal features associated with talking, laughing,and coughing can be identified as respiration events that are associatedwith portions of the set of data. In other examples, features fromaccelerometer and/or gyroscope data can be used to identify andassociate user activities with portions of the dataset. Block S240 canfurther comprise associating a condition of the user's environment(e.g., location, temperature, etc.), derived from the set ofsupplementary signals, with a portion of the dataset and/or the userevent, in order to enrich analyses based upon the dataset. Block S240 ispreferably implemented using an embodiment of the system 100 describedin Section 1 above, and specifically, using a variation of the processordescribed above. However, Block S240 can alternatively be implementedusing any other suitable processing element.

Block S250 recites: generating a metric from the portion of the datasetand a comparative metric based upon the set of data, and functions togenerate metrics and/or trends in metrics based upon the set ofrespiration signals received, the set of supplementary signals received,and any associated respiration events identified within the dataset.Preferably, the metric is determined based upon an algorithmincorporating multiple respiration characteristics captured within theset of respiration signals received in Block S210, such that the metricis a comprehensive metric characterizing an overall state of a user'srespiration state. However, generating a metric in Block S250 canadditionally or alternatively comprise generating a metriccharacterizing a single respiration characteristic (e.g., respirationrate, flow parameter) captured within the set of signals received inBlock S210. The metric is preferably generated in a manner thatincorporates one or more time points of data relevant to a user eventidentified in Block S240, such that the metric characterizes the portionof the dataset associated with the user event.

Preferably, the comparative metric is a trend in the metric determinedfor the portion of the dataset associated with the user event, whereinthe trend in the metric is generated over a time window or subset of atime window during which signals are collected. The time window caninclude times associated with the user event or can omit timesassociated with the user event. Furthermore, the time window ispreferably longer in duration than the duration of the user event, butcan alternatively be shorter or equal in duration to the duration of theuser event. In one example, the comparative metric can include a graphthat plots the metric over a set of time points spanning the timewindow; however, the trend in the metric may alternatively be anyappropriate visual that displays a variation in the metric or time orover any other suitable parameter. In one variation, the comparativemetric can include an average metric, calculated over a time window orsubset of a time window during which signals are collected, which canfacilitate comparisons between a metric associated with a user event,and a comparative (e.g., average metric) associated with other portionsof the dataset. In yet another variation the comparative metric caninclude a metric determined for at least one other occurrence of theuser event. In still another variation, the comparative metric can bederived from signals collected from at least one other user, in order tofacilitate comparisons between users of the same or differentdemographics.

In some variations of Block S250, the metric can be derived from theuser's performance on the task provided in Block S212, such that themetric is not directly calculated from the user's respiration, butalternatively is calculated from the user's performance of a taskindirectly related to the user's respiration. In examples, the metriccan characterize a duration over which the user maintained a desiredrespiration state while performing the task, a variance metric (e.g.,standard deviation, variance) characterizing variations in the user'srespiration state while performing the task, a sociocomparative metriccharacterizing the user's performance of the task relative to pastperformances by the user and/or to one or more additional users, and/orany other suitable performance metric.

Block S260 recites: generating an analysis based upon the user event,the metric, and the trend in the metric, and functions to facilitateassociations between user events and metrics of the user's respirationcharacteristic(s), in a manner that is meaningful to a user. Preferably,the user event is associated with metrics determined at time pointsspanning the user event, such that direct associations can be madebetween user events and metrics (e.g., a metric associated with the userevent and a comparative metric) over time. In one example, a metric thatquantifies the user's breathing efficiency, based upon multiplecharacteristics, can be associated with a user exercise event, such thatthe breathing efficiency metric describes the user's breathingefficiency at time points spanning a user's exercise session. In anotherexample, a metric that quantifies the user's breathing depth can beassociated with a stressful user event (e.g., exam period), such thatthe breathing depth metric describes the user's breathing depth at timepoints spanning a user's exam period. In another example, a graph of ametric (e.g., respiration depth vs. time or comprehensive respirationmetric vs. time) is copresented with indicators of user events (e.g.,sleep periods, stress periods).

In one variation, the analysis can compare a metric associated with auser event with a comparative metric not associated with the user event,such that the analysis provides insight into differences and/orsimilarities between respiration characteristics for different userstates. In one example, the analysis can provide insight intorespiration characteristics of the user while the user is experiencingstress (i.e., the user event) and while the user is not experiencingstress, such that the analysis can inform the user of respirationbehaviors that are associated with the user's stress. In anotherexample, the analysis can provide insight into respirationcharacteristics of the user while the user is performing a task well andwhile the user is not performing a task well, such that the analysis caninform the user of respiration behaviors that are associated withcompetency in performing a task.

In another variation, the analysis can compare a metric associated witha user event, with a comparative metric determined for anotheroccurrence of the user event, such that the analysis facilitatesdetermination respiration behavior changes in relation to repeatperformances of the same user event. In an example, the analysis canprovide insight into the user's respiration behavior associated withrunning over time, such that the user can improve his/her breathingbehavior during running, based on the analysis. In another example, theanalysis can provide insight into the user's respiration behaviorassociated with stress over time, such that the user can track his/herbreathing behavior during periods of stress, based upon the analysis.

Block S270 recites providing a user notification to the user based uponthe analysis, and functions to provide a mechanism to promote change inuser respiration behaviors. The user notification preferably containsinformation relevant to a “respiration status” of the user, and can beassociated with a user event or an anticipated occurrence of a userevent. In some variations, the user notification can indicate a rising,decreasing, or steady level of a metric, and/or a metric that is withinor out of a desired range. The user notification is preferably providedin substantially real time (e.g., within 3 breathing cycles), but insome variations, can be provided in non-real time. Furthermore, the usernotification(s) can be provided continuously, but in some variations,can be provided non-continuously. Furthermore, data from sensors (e.g.,of a supplementary sensing module) can additionally or alternatively beused to generate user notifications that guide the user in monitoringhis/her respiration behavior once sensors indicate that the user is in aspecific environment. For example, data from a GPS and an accelerometercan be used to generate a user notification that guides the user'sbreathing behavior once the GPS and/or accelerometer has indicated thatthe user is exercising within a gym environment. The user notificationcan be provided to the user by way of a messaging client configured totransmit a message to the user, and in examples, can include a textmessaging client, an in-application messaging client, an email client,and any other suitable messaging client. In other examples, the usernotification can be provided to the user in any other suitable manner(e.g., visually rendered, provided in an auditory manner, provided in atactile/haptic manner, etc.). As such, in one application, the usernotification can be provided in substantially real time (e.g., withinthree breathing cycles) at a haptic module (e.g., a module comprising avibration motor) of a respiration monitoring system worn by the user.The user notification can be provided by way of a computing device(e.g., mobile device, tablet, personal computer, etc.) coupled to or incommunication with an embodiment of the system 100 described above;however, the user notification can be provided using any other suitabledevice or element. In one example, the user notification can indicatethat a respiration depth of the user is decreasing upon entering astressful experience, such that the user can adjust his/her breathingbehavior to cope with the stressful experience. In another example, theuser notification can indicate that the user has been in a stressedstate, as indicated in the user's respiration, for a given duration oftime. In another example, the user notification can indicate that theuser's breathing is not efficient (e.g., based upon a breathingefficiency metric) during exercise, such that the user is able to adjusthis/her breathing according to the notification. In some variations, theuser notification can additionally include an explicit directive for theuser to perform a certain action (e.g., breathe deeper, breatheshallower, adjust posture, etc.) that affects the user's respirationpositively. Therefore, the user notification preferably systematicallyand repeatedly facilitates analysis of a respiration status of the userbased upon at least one metric of the user and provides and alert and/oradvice to facilitate management and monitoring of a user's respirationsubstantially in real time.

In some variations of the method 200, wherein the user provides his/herpersonal preferences in the set of supplementary signals, the usernotification provided in Block S270 can be a personalized notificationto perform an activity that affects the user'srespiration/neurocognitive/physiological state based upon the user'spersonal preferences. For example, Block S270 can include providing anotification that the user performs a physical activity that he/sheprefers, in order to reduce a state of stress, as indicated in theanalysis determined in Block S260. In a specific example, if the userhas an affinity toward dancing, and is determined to be in a state ofstress that can be improved by physical activity, the user notificationprovided in Block S270 can recommend that the user take a dancing classat a local gym, or go to a dancing club with acquaintances of the user.In other variations of the example, however, the user notification canrecommend any other suitable activity to the user based upon the user'spersonal preferences.

As shown in FIG. 4, the method 200 can further comprise Block S280,which recites: providing the metric, the trend in the metric, and theassociation to at least one of the user and a second entity. Block S280functions to facilitate monitoring of the user's respiration by thesecond entity. The second entity is preferably a caregiver of the user,such as a parent, family member, health coach, personal trainer,teacher, supervisor, boss, or health care professional servicing theuser; however, the second entity can alternatively be any entity (e.g.,a human, a processing element) monitoring the user's respiration.Preferably, the second entity has access to all analyses provided to theuser, as well as user notifications provided to the user. Additionally,the second entity can have access to analyses and/or notifications formultiple users. In an example, a personal trainer can have access toanalyses an/or notifications for his or her trainees, such that thepersonal trainer can monitor the respiration of multiple patientssimultaneously.

Variations of the system 100 and method 200 include any combination orpermutation of the described components and processes. Furthermore,various processes of the preferred method can be embodied and/orimplemented at least in part as a machine configured to receive acomputer-readable medium storing computer-readable instructions. Theinstructions are preferably executed by computer-executable componentspreferably integrated with a system and one or more portions of thecontrol module 155 and/or a processor. The computer-readable medium canbe stored on any suitable computer readable media such as RAMs, ROMs,flash memory, EEPROMs, optical devices (CD or DVD), hard drives, floppydrives, or any suitable device. The computer-executable component ispreferably a general or application specific processor, but any suitablededicated hardware device or hardware/firmware combination device canadditionally or alternatively execute the instructions.

The FIGURES illustrate the architecture, functionality and operation ofpossible implementations of systems, methods and computer programproducts according to preferred embodiments, example configurations, andvariations thereof. In this regard, each block in the flowchart or blockdiagrams may represent a module, segment, step, or portion of code,which comprises one or more executable instructions for implementing thespecified logical function(s). It should also be noted that, in somealternative implementations, the functions noted in the block can occurout of the order noted in the FIGURES. For example, two blocks shown insuccession may, in fact, be executed substantially concurrently, or theblocks may sometimes be executed in the reverse order, depending uponthe functionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts, or combinations of special purpose hardware andcomputer instructions.

As a person skilled in the art will recognize from the previous detaileddescription and from the figures and claims, modifications and changescan be made to the preferred embodiments of the invention withoutdeparting from the scope of this invention defined in the followingclaims.

What is claimed is:
 1. A system for monitoring respiration comprising: ahousing configured to be attached to clothing worn by a user; arespiration sensor positioned in the housing, the respiration sensorconfigured to generate a respiration signal in response to compressiveforces caused by respiration of the user being applied to the housing;an activity sensor positioned in the housing, the activity sensorconfigured to generate an activity signal associated with activityperformed by the user; and a processor coupled to the respiration sensorand the activity sensor, the processor configured to: transform therespiration signal and the activity signal into a dataset characterizingat least one respiration characteristic of the user and an activitycontemporaneously performed by the user; associate the activitydetermined from the activity signal with a portion of the dataset;extract the at least one respiration characteristic from the dataset bydistinguishing the portion of the dataset associated with the activityfrom a remaining portion of the dataset; analyze the at least onerespiration characteristic and a comparative respiration characteristicgenerated from the remaining portion of the dataset or from anotherdataset; and generate a user notification indicative of respiration ofthe user based on a result of the analysis.
 2. The system of claim 1,wherein the respiration sensor comprises a plurality of conductiveplates separated by a non-rigid material, and wherein the respirationsensor is configured to generate the respiration signal based on achange in capacitance responsive to the compressive forces caused byrespiration of the user being applied to the housing.
 3. The system ofclaim 1, wherein the compressive forces are directed along asuperficial-deep axis through a torso of the user and the housing, andwherein the housing is displaced in a superficial direction from theuser.
 4. The system of claim 2, wherein the plurality of conductiveplates comprises first and second conductive plates, and wherein therespiration sensor is configured to generate the respiration signal inresponse to a deflection of the first plate relative to the second plateand resulting deformation of the non-rigid material.
 5. The system ofclaim 1, wherein the housing is configured to be attached to theclothing proximal to at least one of a chest region or an abdominalregion of the user.
 6. The system of claim 1, further comprising a clipattached to the housing and configured to couple the housing to theclothing, the clip further configured to retain the housing proximal toa body of the user.
 7. The system of claim 1, wherein the processor isfurther configured to transmit the user notification to a remotecomputing device.
 8. The system of claim 1, further comprising a hapticoutput device, and wherein the user notification comprises activation ofthe haptic output device.
 9. The system of claim 1, wherein the at leastone respiration characteristic comprises at least one of depth ofbreath, shallowness of breath, thoracic variations, work of breathing,or phase angle of respiration of the user.
 10. The system of claim 1,wherein the processor is configured to analyze the at least onerespiration characteristic and the comparative respirationcharacteristic generated from the remaining portion of the dataset orfrom another dataset by at least one of: determining at least one of asimilarity or difference from comparison of the at least one respirationcharacteristic with the comparative respiration characteristic generatedfrom the remaining portion of the dataset, the at least one respirationcharacteristic associated with the activity performed by the user andthe comparative respiration characteristic not associated with theactivity; or determining at least one change from comparison of the atleast one respiration characteristic with the comparative respirationcharacteristic generated from another dataset and associated withanother occurrence of the activity performed by the user.
 11. The systemof claim 2, wherein the housing is configured to be positioned betweenthe clothing and a body of the user, and wherein the compressive forcesare configured to deflect at least one of the plurality of conductiveplates in a direction perpendicular to a surface of the body of theuser.
 12. The system of claim 1, wherein the housing comprises asubstantially convex surface configured to face a body of the user. 13.The system of claim 1, wherein the activity sensor comprises anaccelerometer.
 14. The system of claim 1, wherein the respiration sensoris the sole sensor configured to detect respiration of the user.